Bayesian Hierarchical Model for Measuring Reliability in Public Health Surveillance Systems in Ghana

Public health surveillance systems in Ghana are critical for monitoring infectious diseases and managing outbreaks effectively. A Bayesian hierarchical model was developed to measure system reliability, incorporating data from multiple public health units across different regions in Ghana. The model estimated that the overall reliability of the surveillance system was 85%, with significant variation between regions. This study provides a robust method for assessing and enhancing public health surveillance systems in Ghana. Further research should focus on implementing targeted interventions to improve regional disparities identified by this model. Bayesian hierarchical models, Public Health Surveillance Systems, Reliability assessment, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.